Data-Driven Development

How Governments Use Data

From e-government to digital government

How governments use data runs throughout this report, although because it is the subject of a separate World Bank Group report it gets no separate chapter here. Chapter 3 nonetheless focuses on big data for social good, by international, nongovernmental, and humanitarian organizations, as well as by governments.

In the first generations of "e-government," much of the emphasis was on channels ­– using web browsers, and more recently, mobile devices, to access government information and services and to perform transactions. In this period, data was often seen as just the payload of the transaction ­– information supplied by the citizen or the business to support the request for service and the information supplied by the government in return.

However as "e-government" has evolved into "digital government," data is seen increasingly as a strategic asset with value lasting beyond a particular transaction and able to strategically transform the efficiency and effectiveness of government through:

• Making "e-government" transactions more attractive and useful to citizens and businesses by eliminating the need to supply the same information again and again, making transactions more suitable for the mobile channel, and allowing continuity of transactions over time, through different channels, and among different government institutions

• Allowing governments to become more "data driven" at all levels, from policy making through operational management and risk management to individual decision making

• Underpinning the creation of "smart cities" (and "smart nations") whose systems and infrastructure adapt automatically to the needs and behaviors of their inhabitants

• Providing, through "open data" and other programs, authoritative reference, geospatial, and other data to the national economy and society as a whole to improve transparency, to enable economic growth and business innovation, and to increase the engagement of citizens in the co-creation of public services. An example of this would be a National Spatial Data Infrastructure, or Digital Maps.

Viewing government data as a strategic asset leads to requirements for effective and strategic data governance and data management across the entire life cycle of data, including how data is collected, described, and catalogued, as well as secured and controlled (not just to protect confidentiality, but also to ensure availability and integrity). Preparing government data for wider use will require elimination of unnecessary duplication or avoidance of re-collection of data. It will also require a strategic view of how data is shared across government, used within government and other public services, and made available to other economic and societal actors to generate additional economic and social value.

The changing role of national statistical offices

These requirements are in turn leading to demands for new skills and roles, including "data scientists" and "chief data officers," and new functional capabilities such as "data analysis," "big data," and "visualization". Historically, national statistical offices were, appropriately, the central repository of data, along with national archives, as they have the skills and resources to catalogue and manage data. The skills of information scientists and librarians in these offices may not be so readily available to more casual users of data in line ministries. But national statistical offices have had to reinvent themselves in the internet age, in which a simple web search can come up with many more possible sources of information than even the most dedicated librarian can track.

International authorities also need to collaborate on standards for information management. The General Statistical Business Process Model, for example, is a framework for organizing business processes in statistical organizations adopted in more than 60 countries.1 But as national statistical offices modernize and partner with nongovernmental entities that provide data for official statistics, there is recognition that such frameworks and business models may be too rigid. For instance, Statistics New Zealand's 2020 strategy affirms the organization's role as a producer of official statistics but moves beyond this to acknowledge its place in a broader ecosystem and its renewed purpose of "adding value to New Zealand's most important data" through increased data cooperation, integration, and analysis.

The challenge for national statistical offices, therefore, is to ensure the information they hold is properly catalogued (metadata) and easily searchable, and to offer this expertise throughout government. This requires a changing business model for the offices. They can no longer expect to cover costs primarily through sale of publications, though this may still provide an additional source of income. Instead, they must rely on the central treasury for most of their income, and on payment for services provided to other parts of government. Where the central treasury is already overstretched, as in many developing countries, national statistical offices frequently struggle. Thus, just as the value of data is becoming all the more evident in the private sector, it is too often neglected in government, especially at the regional or local level.

Sharing data across government

Data collected and held by one government agency may be valuable to another agency in its operations. For instance, it may relieve the second agency of responsibility for collecting the data itself. And in countries such as Belgium, Estonia, or the Russian Federation the government is not allowed to ask citizens again for data that it has already collected from them.

Of course, if personal or classified data is shared between ministries, it is important that it is shared securely. In the United Kingdom, two compact discs containing personal details of some 25 million children were lost in transit between two government agencies. This led to the mandatory use of encryption when moving confidential data between government agencies.

A number of countries have taken the concept of data sharing further by explicitly recognizing the importance of unified databases accessible to and used across the public sector, rather than each agency keeping its own records. In 2012, Denmark published a strategy for "Good Basic Data for Everyone ­– A Driver for Growth and Efficiency".2 Public authorities in Denmark register various core information about individuals, businesses, real properties, buildings, addresses, and more. This information, called basic data, is seen as important for reuse throughout the public sector because it is an important basis for public authorities to perform their tasks properly and efficiently, "not least because an ever-greater number of tasks have to be performed digitally and across units, administrations and sectors". Some of the registers do not contain personal information and are released as open data (for instance, addresses). In the Netherlands. there is a similar initiative for the sharing of 17 "base registers". The United Kingdom, despite past political controversy, is collaboratively developing a data-sharing policy that will allow the use of key databases across the public sector and, in some circumstances, beyond.

In federated countries those data sets need to be available not just between national agencies, but also regional and municipal agencies. Since changes to master data may first be notified to other agencies, robust processes are essential for the maintenance of the master data using notifications of change as early as possible; this is even more important in federated systems, where important changes, such as of address, may well be notified locally first.

This also exemplifies the increasing extent to which leading governments see databases, not functions, as the key asset of government administration, along with developing strategic plans to introduce interoperability standards and middleware that allow seamless integration of these databases through open application programming interfaces (widely known as APIs).